Every so often I try re-installing R on termux on android to see if it's fixed (some .so doesn't link, even using the latest instructions) but no luck. Last night I was reminded that UserLAnd is another option and hurrah! #rstats, #julialang, #python, and more at my fingertips wherever I go! Great for quick syntax checks/comparisons. Add a BT keyboard and it's a tiny dev machine in my pocket.
#ChatGPT performs better on #Julialang than #Python (and #Rstats) for Large Language Model (#LLM) Code Generation. Why? This blog post shares recent the research and adds a bit of details into where I found LLMs and new language learning having issues.
I wanted to follow along the juliaacademy course "Julia for Data Science", but the first tutorial shows how to activate an environment (?) but in the end I have no idea how to reliably work in an already installed JupyterLab, Julia and packages version compatible, and all in a specific environment for this project.
I've been installing and uninstalling Julia 1.6, 1.9 and 1.10, deleting them from PATH, etc.
With Python is not straightforward, but I got it.
I decided I will use #Plutojl and manually recreate all the courses notebooks. For the sake of learning, it's definitely better than just running readymade cells, plus it's in line with the MIT Julia course.
But it doesn't feel right, I feel there's a huge gap in my understanding, and likely a gap in the tutorials too.
Also, spending 2 days without proper coding, just running around bugs, is super frustrating, just feels like time lost forever to no cause.
Using a raster image as orbit trap to plot a Julia set. The animation illustrates how the fractal structure is changed, as the area of the orbit trap is varying. #fractal#Juliaset#Julialang#image
I made some cards with DataFrames.jl and Luxor.jl. In previous years I used to calculate the data using Astro libraries, but recently I discovered that NASA supply all the relevant data in CSV format. 😂
Introduction time! Hello fediscience members! I'm a new member in this instance, but I'm not new in the fediverse. I migrated from fosstodon.org to this instance. There's nothing wrong, I just needed a place where I can post in English and Spanish. I'm an Assistant Professor at CSU Stan. I usually post about #Rstats, #Quarto , #Linux, #juliaLang, #python, #psychology, #bayesian, #aging, #dementia, #mentalHealth, and other topics that I find interesting in #science.
#SimulatedUniverses
Fresh new visualisation (using #JuliaLang + SAO Ds9) of the evolution of a new massive cluster of galaxies, from z=30 to z=0, simulated with ENZO-MHD (+"my" cosmic rays). The mass is huge (~2e15Msol) and these clusters can only form in very large cosmic volumes, so the whole procedure requires to use aggressive adaptive mesh refinement to cover all necessary range of scales (the size of this "zoom" box is 25Mpc and the max resolution is 15kpc).
Escribir ecuaciones en #LaTeX es bastante pesado. Afortunadamente está el paquete para #Julialang#Latexify.jl. Escribes la fórmula y la transforma en LaTeX de manera muy arreglada. Por ejemplo:
julia> using Latexify
julia> @latexify L = z/(f_hln(10))(10^((T_2-T_ref)/z)-10^((T_1-T_ref)/z))
El paquete de #julialang clapeyron.jl (*) es una pasada para hacer cálculos con funciones de estado para fluidos. Un montón, pero muchos muchos, de modelos disponibles para poder calcular Cp, Cv, U, G y mucho más.
Uso mucho el paquete Unitful.jl para utilizar unidades en #julialang. Si además utilizáis Latexify.jl para que los resultados y cálculos queden bonitos, es imprescindible usar también UnitfulLatexify.jl para que las unidades queden bien.